摘要
为分析铝合金VPPA-MIG复合焊接过程中的电信号,在铝合金7A52复合焊接试验过程中,利用VPPA-MIG复合焊接电信号检测系统分别检测VPPA电弧与MIG电弧电信号,将检测到的电信号经小波降噪处理后进行功率谱分析。通过15组试验的电信号功率谱分析发现MIG电弧电信号中总有0 Hz直流分量存在,而且其功率占整个信号功率比例(功率占比)较大。当VPPA电弧正反极性变化频率恒为100 Hz时,MIG电流越大,MIG电弧电信号的主要高频成分及其谐波分量也越大;焊接速度变化会影响MIG电弧电信号的主要高频成分及其谐波分量的功率占比,而VPPA电流变化不会对MIG电弧电信号的主要高频成分产生影响。VPPA电弧电信号的主要频率成分总包含0 Hz直流分量和100 Hz及其各次谐波分量,且不受自身电弧电流、MIG电弧电流以及焊接速度的影响。
In order to analyze the characteristics of electrical signals in VPPA-MIG hybrid welding of Aluminum alloy. The VPPA arc electric signals and the MIG arc electric signals were acquired by the VPPA-MIG hybrid welding signal Acquisition system,and the power spectrum of the acquisited electrical signals was analyzed after the wavelet de-noising. The DC component is found in the MIG arc electric signals by the power spectrum analysis of the 15 groups of experiment,and its’ power accounts for a large proportion of the power of all frequency components. When the varying frequency of positive and negative polarity of VPPA arc is constant at 100 Hz,main high frequency components of MIG arc electric signals and their harmonic components get greater with the increment of the current of MIG arc. The change of welding speed can affect the power ratio of main high frequency components in MIG arc electric signals and their harmonic components,while the change of the current of VPPA arc cannot affect the main high frequency components of MIG arc. Main frequency components of VPPA arc signals contain DC component,100 Hz and its sub harmonic components,which are not affected by VPPA arc current,MIG arc current and welding speed.
作者
甘世明
韩永全
刘鹏程
包晓艳
Gan Shiming;Han Yongquan;Liu Pengcheng;Bao Xiaoyan(Material Foraning Key Laboratory, Inner Mongolia University of Technology, Hohhot 010051 , China;College of Mechanical Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)
出处
《焊接》
2018年第12期7-11,65,共6页
Welding & Joining
基金
国家自然科学基金资助项目(51665044)
内蒙古自治区博士研究生科研创新项目资助(B20151012810
B20161012804Z)
关键词
复合焊
电信号
小波降噪
功率谱
hybrid welding
MIG arc electric signals
wavelet de-noising
power spectral density